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ObjectiveDescribe dementia cases identified through International Classification of Diseases (ICD) coding in the Long-term Impact of Military-relevant Brain Injury Consortium - Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC) multicenter prospective longitudinal study (PLS) of mild traumatic brain injury (mTBI).DesignDescriptive case series using cross-sectional data.MethodsVeterans Affairs (VA) health system data including ICD codes were obtained for 1563 PLS participants through the VA Informatics and Computing Infrastructure (VINCI). Demographic, injury, and clinical characteristics of Dementia positive and negative cases are described.ResultsFive cases of dementia were identified, all under 65 years old. The dementia cases all had a history of blast-related mTBI and all had self-reported functional problems and four had PTSD symptomatology at the clinical disorder range. Cognitive testing revealed some deficits especially in the visual memory and verbal learning and memory domains, and that two of the cases might be false positives.ConclusionsICD codes for early dementia in the VA system have specificity concerns, but could be indicative of cognitive performance and self-reported cognitive function. Further research is needed to better determine links to blast exposure, blast-related mTBI, and PTSD to early dementia in the military population.

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

Objective: To examine whether post-9/11 veterans who screened positive for mild traumatic brain injury (mTBI) but did not complete a Comprehensive TBI Evaluation (CTBIE) were at higher risk of subsequent adverse events compared with veterans who screened positive and completed a CTBIE. Upon CTBIE completion, information assessed by a trained TBI clinician indicates whether there is mTBI history (mTBI+) or not (mTBI−). Setting: Veterans Health Administration (VHA) outpatient services. Participants: A total of 52 700 post-9/11 veterans who screened positive for TBI were included. The follow-up review period was between fiscal years 2008 and 2019. The 3 groups studied based on CTBIE completion and mTBI status were: (1) mTBI+ (48.6%), (2) mTBI− (17.8%), and (3) no CTBIE (33.7%). Design: This was a retrospective cohort study. Log binomial and Poisson regression models adjusting for demographic, military, pre-TBI screening health, and VHA covariates examined risk ratios of incident outcomes based on CTBIE completion and mTBI status. Main Measures: Incident substance use disorders (SUDs), alcohol use disorder (AUD), opioid use disorder (OUD), overdose, and homelessness documented in VHA administrative records, and mortality as documented in the National Death Index, 3 years post-TBI screen. VHA outpatient utilization was also examined. Results: Compared with the no CTBIE group, the mTBI+ group had 1.28 to 1.31 times the risk of incident SUD, AUD, and overdose, but 0.73 times the risk of death 3 years following TBI screening. The mTBI− group had 0.70 times the risk of OUD compared with the no CTBIE group within the same period. The no CTBIE group also had the lowest VHA utilization. Conclusions: There were mixed findings on risk of adverse events for the no CTBIE group relative to the mTBI+ and mTBI− groups. Future research is needed to explore the observed differences, including health conditions and healthcare utilization, documented outside VHA among veterans who screen positive for TBI. [ABSTRACT FROM AUTHOR]

Introduction: Frontotemporal dementia (FTD) encompasses a clinically and pathologically diverse group of neurodegenerative disorders, yet little work has quantified the unique phenotypic clinical presentations of FTD among post-9/11 era veterans. To identify phenotypes of FTD using natural language processing (NLP) aided medical chart reviews of post-9/11 era U.S. military Veterans diagnosed with FTD in Veterans Health Administration care. Methods: A medical record chart review of clinician/provider notes was conducted using a Natural Language Processing (NLP) tool, which extracted features related to cognitive dysfunction. NLP features were further organized into seven Research Domain Criteria Initiative (RDoC) domains, which were clustered to identify distinct phenotypes. Results: Veterans with FTD were more likely to have notes that reflected the RDoC domains, with cognitive and positive valence domains showing the greatest difference across groups. Clustering of domains identified three symptom phenotypes agnostic to time of an individual having FTD, categorized as Low (16.4%), Moderate (69.2%), and High (14.5%) distress. Comparison across distress groups showed significant differences in physical and psychological characteristics, particularly prior history of head injury, insomnia, cardiac issues, anxiety, and alcohol misuse. The clustering result within the FTD group demonstrated a phenotype variant that exhibited a combination of language and behavioral symptoms. This phenotype presented with manifestations indicative of both language-related impairments and behavioral changes, showcasing the coexistence of features from both domains within the same individual. Discussion: This study suggests FTD also presents across a continuum of severity and symptom distress, both within and across variants. The intensity of distress evident in clinical notes tends to cluster with more co-occurring conditions. This examination of phenotypic heterogeneity in clinical notes indicates that sensitivity to FTD diagnosis may be correlated to overall symptom distress, and future work incorporating NLP and phenotyping may help promote strategies for early detection of FTD. [ABSTRACT FROM AUTHOR]

Background: Studies have demonstrated that individuals diagnosed with traumatic brain injury (TBI) frequently use medical and recreational cannabis to treat persistent symptoms of TBI, such as chronic pain and sleep disturbances, which can lead to cannabis use disorder (CUD). We aimed to determine the Veterans Health Administration (VHA) healthcare utilization and costs associated with CUD and dementia diagnosis in veterans with TBI. Methods: This observational study used administrative datasets from the population of post-9/11 veterans from the Long-term Impact of Military-Relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium and the VA Data Warehouse. We compared the differential VHA costs among the following cohorts of veterans: (1) No dementia diagnosis and No CUD group, (2) Dementia diagnosis only (Dementia only), (3) CUD only, and (4) comorbid dementia diagnosis and CUD (Dementia and CUD). Generalized estimating equations and negative binomial regression models were used to estimate total annual costs (inflation-adjusted) and the incidence rate of healthcare utilization, respectively, by dementia diagnosis and CUD status. Results: Data from 387,770 veterans with TBI (88.4% men; median [interquartile range (IQR)] age at the time of TBI: 30 [14] years; 63.5% white) were followed from 2000 to 2020. Overall, we observed a trend of gradually increasing healthcare costs 5 years after TBI onset. Interestingly, in this cohort of veterans within 5 years of TBI, we observed substantial healthcare costs in the Dementia only group (peak = $46,808) that were not observed in the CUD and dementia group. Relative to those without either condition, the annual total VHA costs were $3,368 higher in the CUD only group, while no significant differences were observed in the Dementia only and Dementia and CUD groups. Discussion: The findings suggest that those in the Dementia only group might be getting their healthcare needs met more quickly and within 5 years of TBI diagnosis, whereas veterans in the Dementia and CUD group are not receiving early care, resulting in higher long-term healthcare costs. Further investigations should examine what impact the timing of dementia and CUD diagnoses have on specific categories of inpatient and outpatient care in VA and community care facilities. [ABSTRACT FROM AUTHOR]

Background: Headache (HA) is a common persistent complaint following mild traumatic brain injury (mTBI), but the association with remote mTBI is not well established, and risk factors are understudied. Objective: Determine the relationship of mTBI history and other factors with HA prevalence and impact among combat-exposed current and former service members (SMs). Design: Secondary cross-sectional data analysis from the Long-Term Impact of Military-Relevant Brain Injury Consortium—Chronic Effects of Neurotrauma Consortium prospective longitudinal study. Methods: We examined the association of lifetime mTBI history, demographic, military, medical and psychosocial factors with (1) HA prevalence (“lately, have you experienced headaches?”) using logistic regression and (2) HA burden via the Headache Impact Test-6 (HIT-6) using linear regression. Each lifetime mTBI was categorized by mechanism (blast-related or not) and setting (combat deployed or not). Participants with non-credible symptom reporting were excluded, leaving N = 1,685 of whom 81% had positive mTBI histories. Results: At a median 10 years since last mTBI, mTBI positive participants had higher HA prevalence (69% overall, 78% if 3 or more mTBIs) and greater HA burden (67% substantial/severe impact) than non-TBI controls (46% prevalence, 54% substantial/severe impact). In covariate-adjusted analysis, HA prevalence was higher with greater number of blast-related mTBIs (OR 1.81; 95% CI 1.48, 2.23), non-blast mTBIs while deployed (OR 1.42; 95% CI 1.14, 1.79), or non-blast mTBIs when not deployed (OR 1.23; 95% CI 1.02, 1.49). HA impact was only higher with blast-related mTBIs. Female identity, younger age, PTSD symptoms, and subjective sleep quality showed effects in both prevalence and impact models, with the largest mean HIT-6 elevation for PTSD symptoms. Additionally, combat deployment duration and depression symptoms were factors for HA prevalence, and Black race and Hispanic/Latino ethnicity were factors for HA impact. In sensitivity analyses, time since last mTBI and early HA onset were both nonsignificant. Conclusion: The prevalence of HA symptoms among formerly combat-deployed veterans and SMs is higher with more lifetime mTBIs regardless of how remote. Blast-related mTBI raises the risk the most and is uniquely associated with elevated HA burden. Other demographic and potentially modifiable risk factors were identified that may inform clinical care. [ABSTRACT FROM AUTHOR]

There is evidence Traumatic Brain Injury (TBI) is associated with increased risk of dementia (D). We compared VA and non-VA facility costs associated with TBI+D and each diagnosis alone, relative to neither diagnosis, annually and over time, 2000–2020. We estimated adjusted panel models of annual VHA costs in VA and non-VA facilities, stratified by age, and by TBI-dementia status. We also estimated cost for the TBI+D cohort by time since TBI and dementia diagnoses. All costs were 2021 inflation adjusted. Veterans <65 ($30,736) and ≥65 ($15,650) with TBI+D, while veterans <65 ($3,379) and ≥65 ($4,252) with TBI-only had higher annual total VHA costs, relative to neither diagnosis. Veterans with TBI+D < 65 ($42,864) and ≥65 ($72,424) had higher costs in years≥15 after TBI diagnosis, while <65 ($36,431) and ≥65 ($37,589) had higher costs in years ≥10 after dementia diagnosis. The main cost driver was inpatient non-VA facility costs. Veterans had continuously increasing inpatient care costs in non-VA facilities over time since their TBI and dementia diagnoses. Given budget constraints on the VA system, quality of care in non-VA facilities warrants comparison with VA facilities to make informed decisions regarding referrals to non-VA facilities. [ABSTRACT FROM AUTHOR]

To assess traumatic brain injury (TBI)-related risks factors for early-onset dementia (EOD). Younger Post-9/11 Veterans may be at elevated risk for EOD due to high rates of TBI in early/mid adulthood. Few studies have explored the longitudinal relationship between traumatic brain injury (TBI) and the emergence of EOD subtypes. This matched case-control study used data from the Veterans Health Administration (VHA) to identify Veterans with EOD. To address the low positive predictive value (PPV = 0.27) of dementia algorithms in VHA records, primary outcomes were Alzheimer's disease (AD) and frontotemporal dementia (FTD). Logistic regression identified conditions associated with dementia subtypes. The EOD cohort included Veterans with AD (n = 689) and FTD (n = 284). There were no significant demographic differences between the EOD cohort and their matched controls. After adjustment, EOD was significantly associated with history of TBI (OR: 3.05, 2.42–3.83), epilepsy (OR: 4.8, 3.3–6.97), other neurological conditions (OR: 2.0, 1.35–2.97), depression (OR: 1.35, 1.12–1.63) and cardiac disease (OR: 1.36, 1.1–1.67). Post-9/11 Veterans have higher odds of EOD following TBI. A sensitivity analysis across TBI severity confirmed this trend, indicating that the odds for both AD and FTD increased after more severe TBIs. [ABSTRACT FROM AUTHOR]

Background: Veterans with posttraumatic epilepsy (PTE), particularly those with comorbidities associated with epilepsy or traumatic brain injury (TBI), have poorer health status and higher symptom burden than their peers without PTE. One area that has been particularly poorly studied is that of the role of caregivers in the health of veterans with PTE and the impact caring for someone with PTE has on the caregivers themselves. Objective: In this study, we aim to address the following: describe and compare the health and quality of life of veterans and caregivers of veterans with and without PTE; evaluate the change in available supports and unmet needs for services among caregivers of post-9/11 veterans with PTE over a 2-year period and to compare support and unmet needs with those without PTE; and identify veteran and caregiver characteristics associated with the 2-year health trajectories of caregivers and veterans with PTE compared with veterans without PTE. Methods: We conducted a prospective cohort study of the health and quality of life among 4 groups of veterans and their caregivers: veterans with PTE, nontraumatic epilepsy, TBI only, and neither epilepsy nor TBI. We will recruit participants from previous related studies and collect information about both the veterans and their primary informal caregivers on health, quality of life, unmet needs for care, PTE and TBI symptoms and treatment, relationship, and caregiver experience. Data sources will include existing data supplemented with primary data, such as survey data collected at baseline, intermittent brief reporting using ecological momentary assessment, and qualitative interviews. We will make both cross-sectional and longitudinal comparisons, using veteran-caregiver dyads, along with qualitative findings to better understand risk and promotive factors for quality of life and health among veterans and caregivers, as well as the bidirectional impact of caregivers and care recipients on one another. Results: This study was approved by the institutional review boards of the University of Utah and Salt Lake City Veterans Affairs and is under review by the Human Research Protection Office of the United States Army Medical Research and Development Command. The Service Member, Veteran, and Caregiver Community Stakeholders Group has been formed and the study questionnaire will be finalized once the panel reviews it. We anticipate the start of recruitment and primary data collection by January 2022. Conclusions: New national initiatives aim to incorporate the caregiver into the veteran's treatment plan; however, we know little about the impact of caregiving--both positive and negative--on the caregivers themselves and on the veterans for whom they provide care. We will identify specific needs in this understudied population, which will inform clinicians, patients, families, and policy makers about the specific impact and needs to equip caregivers in caring for veterans at home. [ABSTRACT FROM AUTHOR]

Objective: To evaluate whether neurobehavioral symptoms differ between groups of veterans with mild traumatic brain injury (mTBI) classified by health characteristics. Participants: A total of 71 934 post-9/11 veterans with mTBI from the Chronic Effects of Neurotrauma Consortium Epidemiology warfighter cohort. Design: Cross-sectional analysis of retrospective cohort. Main Measures: Health phenotypes identified using latent class analysis of health and function over 5 years. Symptom severity measured using Neurobehavioral Symptom Inventory; domains included vestibular, somatic, cognitive, and affective. Results: Veterans classified as moderately healthy had the lowest symptom burden while the polytrauma phenotype group had the highest. After accounting for sociodemographic and injury characteristics, polytrauma phenotype veterans had about 3 times the odds of reporting severe symptoms in each domain compared with moderately healthy veterans. Those veterans who were initially moderately healthy but whose health declined over time had about twice the odds of severe symptoms as consistently healthier Veterans. The strongest associations were in the affective domain. Compared with the moderately healthy group, veterans in other phenotypes were more likely to report symptoms substantially interfered with their daily lives (odds ratio range: 1.3-2.8). Conclusion: Symptom severity and interference varied by phenotype, including between veterans with stable and declining health. Ameliorating severe symptoms, particularly in the affective domain, could improve health trajectories following mTBI. [ABSTRACT FROM AUTHOR]

Mild traumatic brain injury in the Veteran population is frequently comorbid with pain, post-traumatic stress disorder, and/or depression. However, not everyone exposed to mild traumatic brain injury experiences these comorbidities and it is unclear what factors contribute to this variability. The objective of this study was to identify comorbidity phenotypes among Post-9/11 deployed Veterans with no or mild traumatic brain injury and examine the association of comorbidity phenotypes with adverse outcomes. We found that Veterans with mild traumatic brain injury (n = 93,003) and no brain injury (n = 434,378) were mean age of 32.0 (SD 9.21) on entering Department of Veterans Health Administration care, were predominantly Caucasian non-Hispanic (64.69%), and served in the Army (61.31%). Latent class analysis revealed five phenotypes in each subcohort; and phenotypes were common to both. The phenotype was found only in no brain injury. Unique phenotypes in mild traumatic brain injury included , , and . There was substantial variation in adverse outcomes. The phenotype had the lowest likelihood of adverse outcomes. There were no differences between and phenotypes. Phenotypes of comorbidity vary significantly by traumatic brain injury status including divergence in phenotypes (and outcomes) over time in the mild traumatic brain injury subcohort. Understanding risk factors for the divergence between vs. and vs. , will improve our ability to proactively mitigate risk, better understand the early patterns of comorbidity that are associated with neurodegenerative sequelae following mild traumatic brain injury, and plan more patient-centered care. [ABSTRACT FROM AUTHOR]

Objective: To describe change in body mass index (BMI) and weight classification 1-year post- traumatic brain injury (TBI) among Veterans and service members. Design: Prospective observational cohort study. Setting: VA Polytrauma Rehabilitation Centers. Participants: Veterans and service members (N = 84) enrolled in VA Traumatic Brain Injury Model Systems (VA TBIMS) study with BMI scores at enrollment and 1-year post-injury. Interventions: N/A. Main outcome measures: BMI scores from height and weight and weight classifications (underweight, normal weight, overweight, obese classes 1-3) defined by WHO. Results: Twenty per cent were obese at time of injury and 24% were obese at 1-year post-injury. Cross-tab analyses revealed 7% of normal weight and 24% overweight participants at time of injury as obese Class 1 one-year post-injury. Univariate models found BMI and tobacco smoking at time of injury were significant predictors of higher BMI scores 1-year post-TBI. Multivariable models found BMI at time of injury and motor functioning, were significant predictors. Preinjury BMI, tobacco smoking and PTSD symptom severity predicted change in weight category. Conclusion: While obesity among service members and Veterans post-TBI is below national averages, trends in weight gain between time of injury and 1-year follow-up were observed. Implications for health promotion and chronic disease management efforts with regards to rehabilitation for injured military are discussed. List of Abbreviations: BMI, Body mass index; BRFSS, Behavioural Risk Factor Surveillance; GCS, Glasgow Coma Scale; FIM, Functional Independence Measure; NIDILRR, National Institute on Independent Living and Rehabilitation Research; PCL-C, PTSD checklist-civilian; PSTD, Post-traumatic stress disorder; VA, Veterans Affairs; VA PRC, Veterans Affairs Polytrauma Rehabilitation; VA TBIMS, Veterans Affairs TBI Model Systems; [ABSTRACT FROM AUTHOR]

Over the past few decades, the rise of multiple chronic conditions has become a major concern for clinicians. However, it is still not known precisely how multiple chronic conditions emerge among patients. We propose an unsupervised multi-level temporal Bayesian network to provide a compact representation of the relationship among emergence of multiple chronic conditions and patient level risk factors over time. To improve the efficiency of the learning process, we use an extension of maximum weight spanning tree algorithm and greedy search algorithm to study the structure of the proposed network in three stages, starting with learning the inter-relationship of comorbidities within each year, followed by learning the intra-relationship of comorbidity emergence between consecutive years, and finally learning the hierarchical relationship of comorbidities and patient level risk factors. We also use a longest path algorithm to identify the most likely sequence of comorbidities emerging from and/or leading to specific chronic conditions. Using a de-identified dataset of more than 250,000 patients receiving care from the U.S. Department of Veterans Affairs for a period of five years, we compare the performance of the proposed unsupervised Bayesian network in comparison with those of Bayesian networks developed based on supervised and semi-supervised learning approaches, as well as multivariate probit regression, multinomial logistic regression, and latent regression Markov mixture clustering focusing on traumatic brain injury (TBI), post-traumatic stress disorder (PTSD), depression (Depr), substance abuse (SuAb), and back pain (BaPa). Our findings show that the unsupervised approach has noticeably accurate predictive performance that is comparable to the best performing semi-supervised and the second-best performing supervised approaches. These findings also revealed that the unsupervised approach has improved performance over multivariate probit regression, multinomial logistic regression, and latent regression Markov mixture clustering. [ABSTRACT FROM AUTHOR]

Objective: We review health services and reintegration practices that contribute to the rehabilitation of US active duty service members (ADSMs) and Veterans who experienced traumatic brain injury (TBI), especially mild TBI (mTBI), as discussed at the 2015 Department of Veterans Affairs (VA) TBI State-of-the-Art (SOTA) Conference. Methodology: We reviewed the state-of-the-art at the time of the previous 2008 TBI SOTA Conference, advances in the field since then, and future directions to address gaps in knowledge. Main results: We reviewed: (1) mTBI and its comorbid conditions documented in ADSMs and Veterans, and recognized the need for additional healthcare utilization, health cost and quality of care studies; (2) VA vocational rehabilitation programmes and the effectiveness of supported employment for helping those with workplace difficulties; (3) the application of technology to assist in TBI rehabilitation, including mobile device applications for self-management, videoconferencing with providers, and virtual reality to help with behavioural and cognitive challenges, and (4) Department of Defense (DoD)-VA partnerships on identification, evaluation and dissemination of TBI best practices. Conclusions: There have been significant advances in TBI rehabilitation, but multiple areas across the DoD and VA care continuum need further exploration and development to meet the needs of ADSMs and Veterans. [ABSTRACT FROM PUBLISHER]

Objective: Within the same time frame, compare the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) and VA Traumatic Brain Injury Model System (TBIMS) data sets to inform future research and generalizability of findings across cohorts. Setting: Inpatient comprehensive interdisciplinary rehabilitation facilities. Participants: Civilians, Veterans, and active duty service members in the VA (n = 550) and NIDILRR civilian settings (n = 5270) who were enrolled in TBIMS between August 2009 and July 2015. Design: Prospective, longitudinal, multisite study. Main Measures: Demographics, Injury Characteristics, Functional Independence Measures, Disability Rating Scale. Results: VA and NIDILRR TBIMS participants differed on 76% of comparisons (18 Important, 8 Minor), with unique differences shown across traumatic brain injury etiology subgroups. The VA cohort was more educated, more likely to be employed at the time of injury, utilized mental health services premorbidly, and experienced greater traumatic brain injury severity. As expected, acute and rehabilitation lengths of stay were longer in the VA with no differences in death rate found between cohorts. Conclusions: Substantial baseline differences between the NIDILRR and VA TBIMS participants warrant caution when comparing rehabilitation outcomes. A substantive number of NIDILRR enrollees had a history of military service (>13%) warranting further focused study. The TBIMS participant data collected across cohorts can be used to help evidence-informed policy for the civilian and military-related healthcare systems. [ABSTRACT FROM AUTHOR]

To examine whether Veterans who screened positive for mild traumatic brain injury (mTBI), but did not complete a Veterans Health Administration (VHA) Comprehensive TBI Evaluation (CTBIE), were at higher risk for adverse outcomes compared to Veterans who screened negative for TBI. Retrospective longitudinal study that included data from Department of Veterans Affairs (VA), Department of Defense (DoD), and National Death Index. DoD data ranged from October 1, 1999, to September 30, 2019 (Fiscal Years [FYs]2000-2019) and VHA data ranged from October 1, 2001, to September 30, 2019 (FYs2002-2019). The follow-up review period was within 3 years of TBI screening. Veterans Health Administration. Post-9/11 Veterans who were screened for deployment-related mTBI. None. Incident diagnoses of substance use disorder (SUD), alcohol use disorder (AUD), opioid use disorder (OUD), overdose, and homelessness within 3 years of TBI screening. Compared to Veterans who screened negative for TBI, Veterans who screened positive for mTBI but never completed a CTBIE were at increased risk for incident SUD (HR=1.40, 95% CI=1.27-1.54), AUD (HR=1.32, 95% CI=1.19-1.45), OUD (HR=1.68, 95% CI=1.35-2.09), overdose (HR=1.39, 95% CI=1.13-1.70), and homelessness (HR=1.47, 95% CI=1.32-1.65) within 3 years following their TBI screening, after controlling for demographic, military, and regional covariates. Veterans who screened positive for mTBI but did not receive a CTBIE were at increased risk for incident SUD, AUD, OUD, overdose, and homelessness relative to Veterans who screened negative for TBI. This potentially represents missed opportunities for access to interdisciplinary care to identify and address mTBI history and/or other conditions that can diminish health, safety, and quality of life. Prior to military discharge, the DoD should increase educational efforts to discuss the importance of follow-up health care. In VHA, there should be similar messaging, as well as targeted outreach to Veterans who screen positive for mTBI but do not complete a CTBIE within 30 days of screening to minimize the risk of adverse outcomes. The authors have no conflicts to disclose. [ABSTRACT FROM AUTHOR]

Objective: To examine the association of epilepsy with traumatic brain injury (TBI) in Afghanistan and Iraq (Operation Enduring Freedom [OEF]/Operation Iraqi Freedom [OIF]) Veterans. Design: Cross-sectional observational study. Participants: A total 256 284 OEF/OIF Veterans who received inpatient and outpatient care in the Veterans Health Administration in fiscal years 2009-2010. Main Outcome Measures: We used algorithms developed for use with International Classification of Diseases, Ninth Revision, Clinical Modification, codes to identify epilepsy, TBI (penetrating TBI [pTBI]/other TBI), and other risk factors for epilepsy (eg, stroke). TBI and other risk factors were identified prior to the index date (first date of seizure or October 1, 2009) for primary analyses. Results: Epilepsy prevalence was 10.6 per 1000 (N = 2719) in fiscal year 2010; age-adjusted prevalence was 6.1. Of 37 718 individuals with a diagnosis of TBI, 29 297 Veterans had a diagnosis of TBI prior to the index date. Statistically significant associations were found between epilepsy and prior TBI diagnosis (pTBI: adjusted odds ratio = 18.77 [95% confidence interval, 9.21-38.23]; other TBI: adjusted odds ratio = 1.64 [1.43–1.89]). Conclusions: Among OEF/OIF Veterans, epilepsy was associated with previous TBI diagnosis, with pTBI having the strongest association. Because war-related epilepsy in Vietnam War Veterans with TBI continued 35 years postwar, a detailed, prospective study is needed to understand the relationship between epilepsy and TBI severity in OEF/OIF Veterans. [ABSTRACT FROM AUTHOR]

Introduction: Determine the association between acquired stuttering (AS), traumatic brain injury (TBI), and post-traumatic stress disorder (PTSD) in a cohort of 309,675 U.S. Iraq and Afghanistan veterans. The secondary aim was to determine the association between AS and medication patterns for veterans in the sample.Materials and Methods: Retrospective study using data from the Veterans Health Administration National Repository for veterans deployed in support of combat operations in Iraq and Afghanistan and who received Veterans Health Administration care in 2010 and 2011. We identified stuttering using ICD-9 codes to establish the association between AS, TBI, and PTSD, controlling for demographic characteristics and other comorbidities. Multivariable logistic regression was used to determine the association between comorbid conditions and potentially problematic medications associated with stuttering.Results: Two hundred thirty-five veterans (0.08%) were diagnosed with AS in the cohort. There was the greater likelihood of an AS diagnosis for veterans with concomitant TBI and PTSD when compared with veterans without these diagnoses. Over 66% of those with stuttering were prescribed at least one medication that affected speech fluency (antidepressants, anxiolytics, and antiepileptic drugs) compared with 35% of those without AS.Conclusion: Veterans with a comorbid diagnosis of TBI and PTSD were more likely to be diagnosed with AS AOR: 9.77 (95% CI = 6.93-13.78, p < 0.05) and more likely to have been prescribed medications known to affect speech production OR: 3.68 (95% CI = 2.81-4.82, p < 0.05). Clinicians treating veterans with these complex comorbid conditions should consider the impact of medications on speech fluency. [ABSTRACT FROM AUTHOR]